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Clarify scipy linprog transformation description
Clarifies that SciPy transforms the problem into standard form internally after presolve.
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lectures/lp_intro.md

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@@ -487,9 +487,9 @@ The optimal plan tells the factory to produce $2.5$ units of Product 1 and $5$
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We are using the `linprog` function as a *black box*.
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Inside it, Python first transforms the problem into standard form.
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Internally, after a presolve step, SciPy transforms the problem into a standard form before applying the selected solver.
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To do that, for each inequality constraint it generates one slack variable.
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In this transformation, one slack variable is added for each inequality constraint.
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Here the vector of slack variables is a two-dimensional NumPy array that equals $b_{ub} - A_{ub}x$.
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